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Data-driven approaches to improve water-use efficiency and drought resistance in crop plants

OAR@ICRISAT

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Relation http://oar.icrisat.org/12304/
https://www.sciencedirect.com/science/article/abs/pii/S0168945223002698
https://doi.org/10.1016/j.plantsci.2023.111852
 
Title Data-driven approaches to improve water-use efficiency and drought resistance in crop plants
 
Creator Sharma, N
Raman, H
Wheeler, D
Kalenahalli, Y
Sharma, R
 
Subject Drought Tolerance
Data & Analytics
Water Resources
 
Description With the increasing population, there lies a pressing demand for food, feed and fibre, while the changing climatic conditions pose severe challenges for agricultural production worldwide. Water is the lifeline for crop production; thus, enhancing crop water-use efficiency (WUE) and improving drought resistance in crop varieties are crucial for overcoming these challenges. Genetically-driven improvements in yield, WUE and drought tolerance traits can buffer the worst effects of climate change on crop production in dry areas. While traditional crop breeding approaches have delivered impressive results in increasing yield, the methods remain time-consuming and are often limited by the existing allelic variation present in the germplasm. Significant advances in breeding and high-throughput omics technologies in parallel with smart agriculture practices have created avenues to dramatically speed up the process of trait improvement by leveraging the vast volumes of genomic and phenotypic data. For example, individual genome and pan-genome assemblies, along with transcriptomic, metabolomic and proteomic data from germplasm collections, characterised at phenotypic levels, could be utilised to identify marker-trait associations and superior haplotypes for crop genetic improvement. In addition, these omics approaches enable the identification of genes involved in pathways leading to the expression of a trait, thereby providing an understanding of the genetic, physiological and biochemical basis of trait variation. These data-driven gene discoveries and validation approaches are essential for crop improvement pipelines, including genomic breeding, speed breeding and gene editing. Herein, we provide an overview of prospects presented using big data-driven approaches (including artificial intelligence and machine learning) to harness new genetic gains for breeding programs and develop drought-tolerant crop varieties with favourable WUE and high-yield potential traits.
 
Publisher Elsevier
 
Date 2023-09-01
 
Type Article
PeerReviewed
 
Identifier Sharma, N and Raman, H and Wheeler, D and Kalenahalli, Y and Sharma, R (2023) Data-driven approaches to improve water-use efficiency and drought resistance in crop plants. Plant Science (TSI), 336. ISSN 0168-9452